Ryan Gill

662 citations
35 papers · 429 · h-index 11

Impact in

Papers in

Ryan Gill

34 papers receiving 417 citations

Peers

Ryan Gill
Comparison fields: 5 of 103
  • Statistics and Probability 33
  • Cancer Research 53
  • Management Science and Operations Research 45
  • Finance 30
  • Economics and Econometrics 77
Replace Michal Pešta with:
Michal Pešta Czechia
Weichen Wang United States
Ker-Chau Li United States
Zhenjuan Liu China
Yaning Yang China
Egil Ferkingstad Norway
Rafael Weißbach Germany
Corwin Joy United States
Ryan Gill relative to Michal Pešta Czechia Michal Pešta's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ryan Gill

Since Specialization
Citations

This map shows the geographic impact of Ryan Gill's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ryan Gill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan Gill more than expected).

Fields of papers citing papers by Ryan Gill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan Gill. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ryan Gill. The network helps show where Ryan Gill may publish in the future.

Co-authors

The 25 scholars most cited alongside Ryan Gill, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ryan Gill Line = papers co-authored together Ryan Gill links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010110
2 201754
3 201144
4 201035
5 202223
6 200716
7 202115
8 202113
9 202113
10 201412
11 202111
12 201410
13 20038
14 20148
15 20148
16 20146
17 20195
18 20164
19 20064
20 20163

About Ryan Gill

Ryan Gill is a scholar working on Economics and Econometrics, Molecular Biology, Finance, General Economics, Econometrics and Finance and Statistics and Probability, having authored 35 papers that have together received 429 indexed citations. Recurring topics across this work include Market Dynamics and Volatility (10 papers), Gene expression and cancer classification (8 papers), Monetary Policy and Economic Impact (6 papers), Financial Risk and Volatility Modeling (5 papers), Statistical Methods and Inference (4 papers), Bioinformatics and Genomic Networks (4 papers), Advanced Statistical Process Monitoring (4 papers) and Complex Systems and Time Series Analysis (4 papers). The work is most often cited by research in Statistics and Probability (33 citations), Cancer Research (53 citations), Management Science and Operations Research (45 citations), Finance (30 citations) and Economics and Econometrics (77 citations). Ryan Gill has collaborated with scholars based in United States, South Africa and Ghana. Frequent co-authors include Somnath Datta, Susmita Datta, Anokye M. Adam, Xiaohong Li, Nigel G. F. Cooper, Susmita Datta, Jae Keun Yoo, Seongho Kim, Sutirtha Chakraborty and N. Shesh. Their work appears in journals such as IEEE Access, Journal of Statistical Planning and Inference, ˜The œJournal of developing areas, Canadian Journal of Statistics and Operations Research Letters.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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